Discrimination Between Pre‐ and Postcapillary Pulmonary Hypertension Using Platelet RNA

BACKGROUND: Appropriate treatment of pulmonary hypertension (PH) is critically dependent on accurate discrimination between pre‐ and postcapillary PH. However, clinical discrimination is challenging and frequently requires a right heart catheterization. Existing risk scores to detect postcapillary PH have suboptimal discriminatory strength. We have previously shown that platelet‐derived RNA profiles may have diagnostic value for PH detection. Here, we hypothesize that platelet‐derived RNAs can be employed to select unique biomarker panels for the discrimination between pre‐ and postcapillary PH. METHODS AND RESULTS: Blood platelet RNA from whole blood was isolated and sequenced from 50 patients with precapillary PH (with different PH subtypes) as well as 50 patients with postcapillary PH. RNA panels were calculated by ANOVA statistics, and classifications were performed using a support vector machine algorithm, supported by particle swarm optimization. We identified in total 4279 different RNAs in blood platelets from patients with pre‐ and postcapillary PH. A particle swarm optimization–selected RNA panel of 1618 distinctive RNAs with differential levels together with a trained support vector machine algorithm accurately discriminated patients with precapillary PH from patients with postcapillary PH with 100% sensitivity, 60% specificity, 80% accuracy, and 0.95 (95% CI, 0.86–1.00) area under the curve in the independent validation series (n=20). CONCLUSIONS: This proof‐of‐concept study demonstrates that particle swarm optimization/support vector machine–enhanced classification of platelet RNA panels may be able to discriminate precapillary PH from postcapillary PH. This research provides a foundation for the development of a blood test with a high negative predictive value that would improve early diagnosis of precapillary PH and prevents unnecessary invasive testing in patients with postcapillary PH.